New insights into microbial metal resistance by omics-based approaches

Abstract

Aiming to gain a thorough understanding of microbial metal resistance under the current state of metal contamination, with the omics methods, metal resistance genes (MRGs) were explored from different perspectives in this thesis within a framework of environmental relevance. To give a glimpse of genetic characteristics associated with “metallophiles” - Cupriavidus metallidurans, extensive comparison among genomes (including 4 isolates) from the corresponding genus was conducted, revealing the most diverse and compact MRG clusters owned by the species. Moreover, copper enrichment was obtained from activated sludge and analyzed by metagenomics. In addition to particular perturbation of copper stress on community composition, induced shift of resistance genes abundance toward copper efflux system was observed based upon efficient analysis pipeline coupled with the self-constructed copper resistance protein database (CuRD). Given the resolution of a vast number of genomes owning to the recent advent of de novo sequencing platforms, broad-scale MRGs profile and their association with antibiotic resistance genes (ARGs) were investigated through efficient bioinformatic analysis. Significant MRG enrichment was observed in cosmopolitan taxa (e.g. Proteobacteria and Enterobacteriales) and human habitat. Regarding the relationship between MRGs and ARGs in the large genome collection, strong abundance correlation in several phylogenies (e.g. Proteobacteria, Gamaproteobacteria, and Enterobacteriales) and significant genetic co-occurrence in human pathogen species (e.g. Escherichia coli, Salmonella enterica, Shigella flexneri) were discovered. Furthermore, abundance/diversity profiles and similarity patterns of MRGs in 57 metagenomic datasets from 10 typical human-related environmental types were studied. An obvious abundance range was found in different environmental types and specific enrichment was revealed in adult chicken faeces. Distinct environmental types acted as a primary role in shaping similarity grouping in NMDS of the 57 samples. Though the main searching tool utilized in the thesis is similarity-based BLAST, it highly depends on reference sequences thereby restricting prediction of novel genes. Therefore, domain-based profile hidden markov models (HMMs) database - MR.HMMs composed of 60 metal resistance protein families was constructed in this study. By examining precision and recall values, profile specific GA threshold was set as a reliable cutoff rather than e-value. To further optimize performance, public database UniPro/SwissProt was utilized as an independent training set to guarantee excellent retrieval capability for target MRGs. By applying the MR.HMMs-based searching strategy to metagenomic datasets of livestock faeces, higher MRGs annotation percentages were revealed compared with similarity-based BLAST searching. At last, as a preliminary experiment to explore multi-omics application in microbial metal resistance, responses at gene transcription and translation levels in the model strain Escherichia coli K12 were assessed by high-throughput sequencing (HTS)-based metatranscriptome and mass spectrum based metaproteome. The inconsistence between RNA and protein implied remarkable complexity across different biological processes, which substantially limited parallel analysis of results obtained from the two platforms. Differential regulation analysis revealed that toxic effect of silver was mainly characterized in basic function categories, such as basic cellular composition metabolism, energy production, and cell skeleton synthesis.